Part 4

from google.colab import drive
drive.mount('/content/gdrive')
# drive.flush_and_unmount()

Mounted at /content/gdrive

root_path = 'gdrive/My Drive/GLCV_Project/'

print(colored('\x1B[1mPath of dataset from drive.....','blue'))
#!unzip '/content/drive/MyDrive/Files/Part 4 Video.zip' -d '/content/drive/MyDrive/Files/Output/Video Part 4'
print(colored('\x1B[1mNot running again as Unziping is already done....','green'))

import numpy as np
import cv2

%matplotlib inline
from matplotlib import pyplot as plt

np.random.seed(42)

#Routine to fix 
def fixColor(image):
    return(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

!pip install IPython

Requirement already satisfied: IPython in /usr/local/lib/python3.7/dist-packages (5.5.0)
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Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.7/dist-packages (from pexpect; sys_platform != "win32"->IPython) (0.7.0)

#Take a look at the input video
# from IPython.display import Video
from IPython.core.display import Video
Video("/content/gdrive/MyDrive/GLCV_Project/video1.mp4", embed=True)

#Ecxtracting background from the video
video_stream = cv2.VideoCapture('/content/gdrive/MyDrive/GLCV_Project/video1.mp4')

# Get the count of the frame
frameIds = video_stream.get(cv2.CAP_PROP_FRAME_COUNT)
frameIds = int(frameIds)
# Store selected frames in an array

frames = []
for fid in range(frameIds):
    video_stream.set(cv2.CAP_PROP_POS_FRAMES, fid)
    ret, frame = video_stream.read()
    frames.append(frame)
    
# video_stream.release()

writer = cv2.VideoWriter("/content/gdrive/MyDrive/GLCV_Project/output2_P4.mp4", cv2.VideoWriter_fourcc(*"MP4V"), 30,(640,480))

video_mask = []


from google.colab.patches import cv2_imshow

#Eliminating background and highlighting the objects
bcg_img = cv2.createBackgroundSubtractorMOG2(history = 500, varThreshold = 16, detectShadows = False)
for frame in frames:
  mask = bcg_img.apply(frame)
  video_mask.append(mask)

  #Improving the extraction by removing all the smaller elements and focus our attention on objects that are larger than a certain area.
  _, mask = cv2.threshold(mask, 254, 255, cv2.THRESH_BINARY)

  #Finding the contouring pixels of each object in the mask
  contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

  #For each contour, we will the area of the contour and impute a bounding box on the objects where area is more than 500
  for cnt in contours:
        # Calculate area and remove small elements
    area = cv2.contourArea(cnt)
    if area > 500:
      x,y,w,h = cv2.boundingRect(cnt)
      # cv2.drawContours(roi, [cnt], -1, (0, 255, 0), 2)
      cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
  # plt.imshow(fixColor(frame))

  writer.write(cv2.resize(frame,(640,480)))

video_stream.release()
writer.release()

# pip install ffmpeg-python

import ffmpeg
import os
def compress_video(video_full_path, output_file_name, target_size):
    # Reference: https://en.wikipedia.org/wiki/Bit_rate#Encoding_bit_rate
    min_audio_bitrate = 32000
    max_audio_bitrate = 256000

    probe = ffmpeg.probe(video_full_path)
    
    # Video duration, in s.
    duration = float(probe['format']['duration'])

    # Target total bitrate, in bps.
    target_total_bitrate = (target_size * 1024 * 8) / (1.073741824 * duration)

    video_bitrate = target_total_bitrate

    i = ffmpeg.input(video_full_path)
    ffmpeg.output(i, os.devnull,
                  **{'c:v': 'libx264', 'b:v': video_bitrate, 'pass': 1, 'f': 'mp4'}
                  ).overwrite_output().run()
    ffmpeg.output(i, output_file_name,
                  **{'c:v': 'libx264', 'b:v': video_bitrate, 'pass': 1, 'f': 'mp4'}
                  ).overwrite_output().run()

compress_video('/content/gdrive/MyDrive/GLCV_Project/output2_P4.mp4', '/content/gdrive/MyDrive/GLCV_Project/output2_P4_compressed.mp4', 10 * 1000)

from IPython.core.display import HTML
from base64 import b64encode
video_path = '/content/gdrive/MyDrive/GLCV_Project/output2_P4_compressed.mp4'

mp4 = open(video_path,'rb').read()
decoded_vid = "data:video/mp4;base64," + b64encode(mp4).decode()
HTML(f'<video width=640 controls><source src={decoded_vid} type="video/mp4"></video>')

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
<ipython-input-1-a49a70b92231> in <module>()
      3 video_path = '/content/gdrive/MyDrive/GLCV_Project/output2_P4_compressed.mp4'
      4 
----> 5 mp4 = open(video_path,'rb').read()
      6 decoded_vid = "data:video/mp4;base64," + b64encode(mp4).decode()
      7 HTML(f'<video width=640 controls><source src={decoded_vid} type="video/mp4"></video>')

FileNotFoundError: [Errno 2] No such file or directory: '/content/gdrive/MyDrive/GLCV_Project/output2_P4_compressed.mp4'